The method is specifically intended for filter-based spectrometers, which typically comprises an infrared light source, and an infrared detector, and there between a number of optical filters, which may be inserted into the optical light path. A sample measurement cell comprising two glass plates defining a storage space therein between for storage of a sample to be analysed, is arranged between the light source and the detector. During use, the cell is filled with the sample e.g. milk, and the light transmitted from the light source through the sample is detected.
Typically, the concentration of the constituent e.g. of fat in milk is determined by use of a number of specific filters from the absorbance in the milk sample measured relative to a reference, such as a reference sample, e.g. a sample of pure water. This is a well-known technique, e.g. as described in U.S. Pat. No. 4,236,075, which has been applied for analysis of food products for more than 20 years.
The analysis of milk is now increasingly being carried out by use of FTIR instruments covering a broad frequency range of the IR spectrum, c.f. international patent application No. PCT/DK96/00068 published as WO 96/24832. The measured spectra of a plurality of known samples are used to let the instrument “learn” how to interpret newly measured spectra of unknown samples. Such learning can be accomplished by multivariate calibration in several ways, e.g. by Principal Component Regression (PCR), Partial Least Squares regression (PLS), Multiple Linear Regression (MLR), Artificial Neural Network (ANN), etc. A great advantage when using FTIR instruments is that such instruments may be standardised so that the same calibration can be applied to a plurality of standardised instruments.
FTIR instruments are costly. Accordingly, there is still a need for the less expensive filter instruments applying a few or at least a limited number of optical filters. It has so far been impossible to standardise such instruments, implying that every instrument must be calibrated separately, and when a measurement cell or any other change in the optical system has been carried out during maintenance, the instrument requires new calibrations.
In this context a calibration means the derivation of a mathematical expression, such as a functional relationship, enabling a prediction of a concentration of a specified constituent from a number of determined absorbance values.
The absorbance, a, is defined as the absorption relative to a reference. The absorbance is determined from signals Is, Io, measured by a detector, (e.g. as a measure in mV or mA), when measuring an unknown sample and a reference, respectively.a=log10(I0/Is)
When the absorbance values, a, have been determined for at least one, preferably a plurality of filters, e.g. four filters, the concentration c of a specific component may be predicted from an expression such as:c=b1*a1+b2*a2+b3*a3+b4*a4 
The b-coefficients in the above equation may be determined by multivariate calibration after measuring a number of samples having various known concentrations of specific constituents. Calibrations are made for specific constituents, e.g. the fat content in milk.
The task of providing a good calibration for an instrument can be very laborious as it usually requires a great number of calibration samples having known concentration of a constituent in question. The calibration samples typically have to be analysed by tedious conventional methods and accordingly, a calibration sample is typically expensive. Since the calibration sample is typically a food product, e.g. a diary product, the durability is rather limited and new test samples have to be provided for each calibration.
Often, a calibrated instrument has to be re-calibrated from time to time. As an example, parts of the instrument, e.g. the cuvette or a detector may be replaced during repair or service. The new part may have a characteristic different from the characteristic of the previous part and accordingly, the relationship between the detected signal and the concentration of the constituent is different.